Semi Senior​/Senior Data Engineer; AWS, Python & SQL

Remote Flexibility: Devsu explicitly promotes a remote-friendly culture, making this role a strong candidate for location-independent work. However, since the company serves US and Lat Am clients, expect some overlap with US Eastern or Central time zones for meetings and collaboration. Full async is unlikely for a senior role involving architecture discussions and mentoring.

Location Constraints: The role is hinted at Honduras, suggesting the company hires across Latin America. If you hold a passport from a LATAM country, you may work from destinations offering digital nomad visas such as:

• Costa Rica – "Rentista" or digital nomad visa, stable infrastructure, UTC-6
• Colombia (Medellín) – Digital nomad visa available, low cost of living ~$1,200–1,800/month, UTC-5
• Portugal (Lisbon) – EU D8 digital nomad visa, though timezone overlap with US clients requires late-evening hours

Perks for Nomads: No specific coworking stipend or equipment budget is mentioned, but access to AI tools and a flexible PTO policy are nomad-friendly. The long-term contract nature provides income stability for visa applications requiring proof of income.

Practical Tip: Prioritize LATAM hubs (Medellín, Mexico City, Buenos Aires) to maintain comfortable US timezone overlap without sacrificing quality of life or cost efficiency.

We are looking for a Senior Data Engineer to design, build, and optimize scalable data platforms that support analytics, ecommerce, logistics, and marketing initiatives. This role is responsible for developing robust data pipelines, improving data infrastructure, and ensuring high-quality, reliable data solutions in an AWS environment. The ideal candidate has strong expertise in Python, SQL, Spark, Airflow, and cloud-based data architectures, along with excellent communication skills and a collaborative mindset.

Responsibilities

• Design, build, and maintain scalable data pipelines for analytics, ecommerce, logistics, and marketing.
• Improve and maintain the company's data infrastructure and tooling, including Redshift/Snowflake, Airflow, and Fivetran.
• Architect data processing systems capable of handling complex data flows and large-scale datasets.
• Develop reliable, efficient, and cost-effective data solutions in an AWS environment.
• Ensure high standards of data quality through automation and best engineering practices.
• Optimize platform performance, resiliency, scalability, and operational costs.
• Collaborate closely with software engineers, analysts, and business stakeholders.
• Mentor engineers and analysts on data engineering best practices.
• Participate in architecture discussions and technical decision-making.

Requirements

Must Have

• 4+ years of experience as a Data Engineer working with modern data technologies.
• Strong proficiency in Python and SQL
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• Hands-on experience with Apache Spark and Apache Airflow
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• Experience designing and architecting data processing systems in AWS
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• Experience with Redshift and/or Snowflake
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• Knowledge of Fivetran or similar data ingestion tools.
• Strong understanding of data quality, automation, and data engineering best practices.
• Excellent communication and interpersonal skills.

Nice to Have

• Experience with streaming technologies such as Kafka or AWS Kinesis Firehose
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• Knowledge of Docker and/or Kubernetes
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• Familiarity with Ruby or R.
• Experience building or migrating a Data Warehouse.
• Experience leading projects or mentoring technical teams.
• A stable, long-term contract with opportunities for career growth.
• Private health insurance.
• A remote-friendly culture that promotes work-life balance.
• Continuous training, mentorship, and learning programs to keep you at the forefront of the industry.
• Free access to AI training resources and…